End of training

README.md

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+---
+license: cc-by-nc-4.0
+base_model: MCG-NJU/videomae-base-finetuned-kinetics
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: VideoMAEF-finetuned-ARSL-diverse-dataset
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# VideoMAEF-finetuned-ARSL-diverse-dataset
+
+This model is a fine-tuned version of [MCG-NJU/videomae-base-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-base-finetuned-kinetics) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0012
+- Accuracy: 1.0
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2.5e-05
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- training_steps: 2395
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.0485        | 0.12  | 298  | 1.1148          | 0.6854   |
+| 0.7256        | 1.12  | 596  | 0.1032          | 1.0      |
+| 0.2052        | 2.12  | 894  | 0.0057          | 1.0      |
+| 0.0451        | 3.12  | 1192 | 0.0028          | 1.0      |
+| 0.1821        | 4.12  | 1490 | 0.0020          | 1.0      |
+| 0.0965        | 5.12  | 1788 | 0.0015          | 1.0      |
+| 0.0873        | 6.12  | 2086 | 0.0012          | 1.0      |
+| 0.0027        | 7.12  | 2384 | 0.0011          | 1.0      |
+| 0.1222        | 8.0   | 2395 | 0.0012          | 1.0      |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.1.2
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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